Special Issue Editor

Special Issue Information

Dear Colleagues,

One of the major keywords in the current digital world is Blockchain, which is playing a major part in all kinds of advanced service systems, offering more convenience, better efficiency/effectiveness by controlling system hardware intelligently in a way humans have never experienced.

Blockchain is also playing an essential part in the healthcare or bioelectronics industry, where enhanced service function and sophistication have become a critical factor in a keen completion. Thus, this Special Issue (SI) focuses on its contributing factors to human society and provides an opportunity for discussions on the relevant convergence technologies. Manuscripts may discuss their technological aspects, usefulness, and contributing factors of their respective Blockchain-based electronic solutions after choosing a suitable subject from the list below or select other ones if needed.

Electronic Blockchain service prioritizing human beings and their lives;

Electronic solutions adopting Blockchain and/or Big Data;

Means of aiding and serving people in need, especially for those disabled or elderly;

Electronic engineering/mathematical/Blockchain theories that would greatly affect science and industry;

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access monthly journal published by MDPI.

From the last decade, pharmaceutical companies are facing difficulties in tracking their products during the supply chain process, allowing the counterfeiters to add their fake medicines into the market. Counterfeit drugs are analyzed as a very big challenge for the pharmaceutical industry worldwide.
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From the last decade, pharmaceutical companies are facing difficulties in tracking their products during the supply chain process, allowing the counterfeiters to add their fake medicines into the market. Counterfeit drugs are analyzed as a very big challenge for the pharmaceutical industry worldwide. As indicated by the statistics, yearly business loss of around $200 billion is reported by US pharmaceutical companies due to these counterfeit drugs. These drugs may not help the patients to recover the disease but have many other dangerous side effects. According to the World Health Organization (WHO) survey report, in under-developed countries every 10th drug use by the consumers is counterfeit and has low quality. Hence, a system that can trace and track drug delivery at every phase is needed to solve the counterfeiting problem. The blockchain has the full potential to handle and track the supply chain process very efficiently. In this paper, we have proposed and implemented a novel blockchain and machine learning-based drug supply chain management and recommendation system (DSCMR). Our proposed system consists of two main modules: blockchain-based drug supply chain management and machine learning-based drug recommendation system for consumers. In the first module, the drug supply chain management system is deployed using Hyperledger fabrics which is capable of continuously monitor and track the drug delivery process in the smart pharmaceutical industry. On the other hand, the N-gram, LightGBM models are used in the machine learning module to recommend the top-rated or best medicines to the customers of the pharmaceutical industry. These models have trained on well known publicly available drug reviews dataset provided by the UCI: an open-source machine learning repository. Moreover, the machine learning module is integrated with this blockchain system with the help of the REST API. Finally, we also perform several tests to check the efficiency and usability of our proposed system.
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This paper seeks to use artificial intelligence blockchain algorithms to ensure safe verification of medical institution PHR data and accurate verification of medical data as existing vulnerabilities. Artificial intelligence has recently spread and has led to research on many technologies thanks to the
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This paper seeks to use artificial intelligence blockchain algorithms to ensure safe verification of medical institution PHR data and accurate verification of medical data as existing vulnerabilities. Artificial intelligence has recently spread and has led to research on many technologies thanks to the Fourth Industrial Revolution. This is a very important factor in healthcare as well as the healthcare industry’s position. Likewise, blockchain is very safe to apply because it encrypts and verifies these medical data in case they are hacked or leaked. These technologies are considered very important. This study raises the problems of these artificial intelligence blockchains and recognizes blockchain, artificial intelligence, neural networks, healthcare, etc.; these problems clearly exist, so systems like EHR are not being used. In the future, ensuring privacy will be made easier when these EHRs are activated and data transmission and data verification between hospitals are completed. To overcome these shortcomings, we define an information security blockchain artificial intelligence framework and verify blockchain systems for accurate extraction, storage, and verification of data. In addition, various verification and performance evaluation indicators are set to obtain the TPS of medical data and for the implementation of standardization work in the future. This paper seeks to maximize the confidentiality of blockchain and the sensitivity and availability of artificial intelligence.
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